machine learning engineer

Matthew Sabino

MACHINE LEARNING ENGINEER

************@*****.*** +60 (3) 2161 0518

Kuala Lumpur, Wilayah Persekutuan 50450, Malaysia

Profile

Innovative Machine Learning Engineer with over 7 years of experience in designing, developing, testing, and deploying applications. Skilled in programming, algorithm design, and building advanced neural networks across multiple languages. Demonstrates a strong passion for machine learning, backed by deep expertise in ML concepts and related technologies. Specialized in analyzing requirements and translating them into scalable, high-performance technical solutions using C#, C++, JavaScript, Python, and other tools to continuously advance Al capabilities.

Professional Experience

Machine Learning Engineer, Stack Intellect(remote) Engineered and fine-tuned machine learning and statistical modeling algorithms, increasing system performance and prediction accuracy by 35% while cutting data processing time by 0%.

Partnered with Adobe's research teams to translate cutting-edge research into commercial-grade Al solutions, contributing to 3+ product launches that improved user engagement by 25%.

01/2023 – 09/2025

Beachwood, Ohio 44122,

US

Designed, simulated, and refined predictive algorithms for electrical load and generation forecasting, boosting precision by 18% and reducing model error rates by 22%.

Collaborated with senior managers to define machine learning objectives and built data-driven forecasting models analyzing 10M+ records, resulting in a 30% improvement in decision-making efficiency.

Architected and deployed automated Al systems enabling 2/7 self-learning predictive capabilities, reducing manual intervention by 60%. Enhanced multi-layered data pipelines and streamlined existing ML frameworks

(TensorFlow, PyTorch), achieving a 2.5x speed-up in model training and 20% better inference latency.

Prototyped and evaluated 5+ proof-of-concept (POC) solutions to validate business hypotheses, earning 90%+ stakeholder approval for pilot-to-production transitions. Machine Learning Engineer, Network Corp(remote)

Designed and implemented molecular dynamics simulations enhanced by machine learning algorithms to precisely detect and characterize protein-DNA interactions. Analyzed over 300 complex simulation datasets using advanced statistical methods. 12/2018 – 11/2022

Carlsbad,CA 92008, US

Elevated simulation accuracy by 30% through the implementation of advanced algorithms.

Devised dimensional data models to meet OLAP requirements. Junior SQL Developer, SummitCore IT Services(remote) Updated and refactored stored procedures using T-SQL to optimize performance. Built PL/SQL stored procedures, functions, and style sheets to reduce data retrieval time by 50%.

09/2017 – 10/2018

Dallas, Texas 75201, US

Re-structured database schemas with 100+ tables to improve data integrity. Education

Ph.D. / Machine Learning, Carnegie Mellon

Research paper: Machine Learning, Probabilities Explained published in Journal of Cryptology. June 2017

Senior data mining project written up in TechCrunch. 2013 – 2017

Pittsburgh, PA

Excelled in database and data Structure coursework. M.D./ Machine Learning, Carnegie Mellon 2011 – 2013 Pittsburgh, PA

Bachelor of Science / Computer Science, University of Washington 2007 – 2011 Washington, WA 98195

Skills

Data and Quantitative Analysis

Decision Analytics

Predictive Modeling

Data-Driven Personalization

Machine Learning Algorithms

Understanding of technical documentation

Communication and presentation

Languages

English Bahasa Malaysia

Contact this candidate